mosaicmpi.cnmf.cNMF.get_nmf_iter_params

mosaicmpi.cnmf.cNMF.get_nmf_iter_params#

cNMF.get_nmf_iter_params(ks, n_iter=100, random_state_seed=None, beta_loss='kullback-leibler', alpha_usage=0.0, alpha_spectra=0.0, init='random')#

_summary_

Parameters:

  • ks (integer or list-like) – Number of topics (components) for factorization. Several values can be specified at the same time, which will be run independently.

  • n_iter (int, optional) – Number of iterations for factorization. If several k are specified, this many iterations will be run for each value of k. defaults to 100

  • random_state_seed (int, optional) – Seed for sklearn random state. defaults to None

  • beta_loss (str, optional) – defaults to ‘kullback-leibler’

  • alpha_usage (float, optional) – Regularization parameter for NMF corresponding to alpha_W in scikit-learn, defaults to 0.0

  • alpha_spectra (float, optional) – Regularization parameter for NMF corresponding to alpha_H in scikit-learn, defaults to 0.0

  • init (str, optional) – defaults to ‘random’

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